Data-science Libraries

264 Components & Libraries

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Data-science Libraries

scikit-learn: machine learning in Python

It is currently maintained by a team of volunteers. scikit-learn requires: You can check the latest sources with the command: The project is currently maintained by a team of volunteers.

Apache Superset is a Data Visualization and Data Exploration Platform

A modern, enterprise-ready business intelligence web application. Superset is a modern data exploration and data visualization platform. Superset can replace or augment proprietary business intellige…

12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all

Travel with us around the world as we apply these classic techniques to data from many areas of the world. Each lesson includes pre- and post-lesson quizzes, written instructions to complete the less…

Learn how to responsibly develop, deploy and maintain production machine learning applications.

Learn the foundations of machine learning through intuitive explanations, clean code and visualizations. Learn how to combine machine learning with software engineering to build production-grade appl…

Probabilistic-Programming-and-Bayesian-Methods-for-Hackers

aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)

After some recent success of Bayesian methods in machine-learning competitions, I decided to investigate the subject again. Even with my mathematical background, it took me three straight-days of rea…

Data Apps & Dashboards for Python. No JavaScript Required.

With Dash Open Source, Dash apps run on your local laptop or workstation, but cannot be easily accessed by others in your organization. Scale up with Dash Enterprise when your Dash app is ready for d…

Create UIs for your machine learning model in Python in 3 minutes

Gradio is an open-source Python library that is used to build machine learning and data science demos and web applications. With Gradio, you can quickly create a beautiful user interface around your …

🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.

Contributions are encouraged and always welcome! If you like to add or update projects, choose one of the following ways:

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

To install the current release: Participating discussions via the following IM groups is also welcomed. Over the past few years, NNI has received thousands of feedbacks on GitHub issues, and pull req…

500 AI Machine learning Deep learning Computer vision NLP Projects with code

The "Python Machine Learning (1st edition)" book code repository and info resource

What you can expect are 400 pages rich in useful material just about everything you need to know to get started with machine learning ... from theory to the actual code that you can directly put into…

An open-source NLP research library, built on PyTorch.

An Apache 2.0 NLP research library, built on PyTorch, for developing state-of-the-art deep learning models on a wide variety of linguistic tasks. When you're ready to start your project, we…

Free online textbook of Jupyter notebooks for fast.ai Computational Linear Algebra course

We start with a high level overview of some foundational concepts in numerical linear algebra. We will use the newsgroups dataset to try to identify the topics of different posts. We use a term-docu…

A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

TPOT will automate the most tedious part of machine learning by intelligently exploring thousands of possible pipelines to find the best one for your data. Once TPOT is finished searching (or you get…

Best Practices, code samples, and documentation for Computer Vision.

In recent years, we've see an extra-ordinary growth in Computer Vision, with applications in face recognition, image understanding, search, drones, mapping, semi-autonomous and autonomous vehicles. A…

Data-centric declarative deep learning framework

The configuration declares the input and output features, with their respective data types. Users can also specify additional parameters to preprocess, encode, and decode features, load from pre-trai…

Open Machine Learning Course

mlcourse.ai is still in self-paced mode but we offer you Bonus Assignments with solutions for a contribution of $17/month. The idea is that you pay for ~1-5 months while studying the course materials…

Modin: Scale your Pandas workflows by changing a single line of code

By simply replacing the import statement, Modin offers users effortless speed and scale for their pandas workflows: If you want to install Modin with a specific engine, we recommend: Modin automatica…

A collection of machine learning examples and tutorials.

A collection of machine learning examples and tutorials. Please note that not all code from all courses will be found in this repository. Some newer code examples (e.g. most of Tensorflow 2.0) were d…

An open-source, low-code machine learning library in Python

PyCaret is an open-source, low-code machine learning library in Python that automates machine learning workflows. It is an end-to-end machine learning and model management tool that speeds up the exp…

A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

Install CatBoost by following the guide for the Next you may want to investigate: If you cannot open documentation in your browser try adding yastatic.net and yastat.net to the list of allowed domain…

python-machine-learning-book-2nd-edition

The "Python Machine Learning (2nd edition)" book code repository and info resource

published September 20th, 2017 Oh, there are so many things that we improved or added; where should I start!? The one issue on top of my priority list was to fix all the nasty typos that were introdu…

A curated list of applied machine learning and data science notebooks and libraries across different industries (by @firmai)

An orchestration platform for the development, production, and observation of data assets.

Dagster is an orchestrator that's designed for developing and maintaining data assets, such as tables, data sets, machine learning models, and reports. You declare functions that you want to run and …

An open source python library for automated feature engineering

Install with pip You can install add-ons individually or all at once by running Below is an example of using Deep Feature Synthesis (DFS) to perform automated feature engineering. In this example, we…

:rocket: Build and manage real-life data science projects with ease!

Metaflow is a human-friendly Python/R library that helps scientists and engineers build and manage real-life data science projects. Metaflow was originally developed at Netflix to boost productivity …

A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning

imbalanced-learn requires the following dependencies: Additionally, imbalanced-learn requires the following optional dependencies: The examples will requires the following additional dependencies: im…

H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

(Note: There is only one issue tracking system for the project. GitHub issues are not enabled; you must use JIRA.) GitHub JIRA -- file bug reports / track issues here Stack Overflow -- ask all code/…

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